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  Threshold extraction in metabolite concentration data

Floeter, A., Nicolas, J., Schaub, T., & Selbig, J. (2004). Threshold extraction in metabolite concentration data. In Bioinformatics (pp. 1491-1494).

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Floeter, A.1, Author
Nicolas, J.1, Author
Schaub, T.1, Author
Selbig, J.2, Author              
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1External Organizations, ou_persistent22              
2BioinformaticsCRG, Cooperative Research Groups, Max Planck Institute of Molecular Plant Physiology, Max Planck Society, ou_1753315              

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Free keywords: *Algorithms Computer Simulation Differential Threshold/*physiology Energy Metabolism/physiology Gene Expression Profiling/methods Gene Expression Regulation, Plant/*physiology Homeostasis/physiology *Models, Biological Plant Proteins/*metabolism Signal Transduction/*physiology Solanum tuberosum/*metabolism
 Abstract: Motivation: Continued development of analytical techniques based on gas chromatography and mass spectrometry now facilitates the generation of larger sets of metabolite concentration data. An important step towards the understanding of metabolite dynamics is the recognition of stable states where metabolite concentrations exhibit a simple behaviour. Such states can be characterized through the identification of significant thresholds in the concentrations. But general techniques for finding discretization thresholds in continuous data prove to be practically insufficient for detecting states due to the weak conditional dependences in concentration data. Results: We introduce a method of recognizing states in the framework of decision tree induction. It is based upon a global analysis of decision forests where stability and quality are evaluated. It leads to the detection of thresholds that are both comprehensible and robust. Applied to metabolite concentration data, this method has led to the discovery of hidden states in the corresponding variables. Some of these reflect known properties of the biological experiments, and others point to putative new states.

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Language(s): eng - English
 Dates: 2004
 Publication Status: Published in print
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 Identifiers: ISI: ISI:000222402400004
DOI: 10.1093/bioinformatics/bth107
URI: ://000222402400004 http://bioinformatics.oxfordjournals.org/content/20/10/1491.full.pdf
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Title: Bioinformatics
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Title: Bioinformatics
Source Genre: Proceedings
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Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 1491 - 1494 Identifier: -